1. Field of the Invention
The present invention relates to an apparatus for and a method of extracting a changed component on a moving picture as time series information, which corresponds to a significant improvement over conventional displacement sensors.
In various types of fields of industrial utility, the present invention makes it possible to measure slight displacement, analyze a linear motion, a rotary motion or a combination of the motions, analyze vibration, count frequencies, and recognize the state of an equipment, for example. On a production and/or processing line of predetermined products, the present invention makes it possible to detect defective products out of the products, and judge the tone of color and the sorting of the products. Even when living organisms are used as objects, it is possible to treat the growth of plants and the physiological phenomena and the actions of animals as time series signals. If the signals are utilized in the succeeding control system, it is feasible to control the position and the attitude, send alarms, start a transfer protocol of the signals or perform predetermined programmed work while holding feedback to the object.
So long as a moving picture is obtained as in cases such as a case where the operating states of domestic equipments, industrial equipments, constructional equipments and facilities on a production line of a factory are grasped and controlled, a case where the traffic conditions of an area are grasped and controlled, a case where the actions and the physiological states of human beings, animals and plants are grasped and a case where the dispensation of medicine, the supply of feed and the spraying of fertilizer are controlled, the present invention can be applied to the grasp of conditions and the prediction of abnormalities in various types of setting with respect to a desired phenomenon throughout all ranges of objects.
2. Description of the Prior Art
Examples of a displacement sensor for extracting a changed component of an object include a mechanical displacement sensor, an eddy current displacement sensor, a laser displacement sensor, and an ultrasonic displacement sensor. In the field of measurements of displacement using input of a video camera, there is a method which is referred to as computer vision. Conventional techniques will be described with respect to the displacement sensors.
The mechanical displacement sensor is a sensor whose part is brought into contact with an object to directly measure displacement. One example is a differential transformer. The differential transformer comprises three coils. A core connected to a metal portion in direct contact with the object is linearly moved in the coils. An AC current is caused to flow in the central coil, and signals are differentially taken out of the right and left coils by applying the principle of electromagnetic induction, to detect the position of the core.
In the eddy current displacement sensor, an AC voltage is previously applied to a coil wound around an insulator. If an object to be measured which is composed of a conductor is brought near the eddy current displacement sensor, an eddy current is produced in the conductor by an AC magnetic field formed by the coil. The eddy current varies depending on the distance from the displacement sensor to the object. The displacement sensor detects the position and the displacement of the object by measuring the change in a voltage excited in the coil.
The laser displacement sensor is a sensor for measuring the displacement of an object utilizing interference of laser light. The principle is essentially the same as that of a Michelson interferometer. Specifically, laser light is divided into reflected light and transmitted light by a semi-transparent mirror. The reflected light is reflected by a fixed reflector and then, converges on a photodetector, while the transmitted light is reflected by a moving reflector and then, converges on the photodetector. Since two beams of light are incident on the photodetector, interference fringes are formed on the surface of the photodetector. The number of interference fringes crossing one point on the surface of the photodetector is counted, thereby to make it possible to measure the distance at which the moving reflector is moved.
The ultrasonic displacement sensor detects the position and the displacement of an object utilizing the time when ultrasonic waves propagate in a medium such as a gas, a liquid, a solid or a living organism, the Doppler effect and interference.
Furthermore, a technique referred to as computer vision is known as a technique for treating an image inputted by a CCD (Charge Coupled Device) sensor or the like and extracting space information so as to measure the motion and the shape of a moving object utilizing an image processing technique. This is used for observing the motion and the shape of the moving object in the steps of extracting particular points related to the shape of the moving object from one or a plurality of images at the same time by a complicated algorithm for mathematically solving various types of simultaneous equations and establishing a correspondence between their values and an actual three-dimensional space to reconstruct information on the three-dimensional space.
Contrary to the conventional techniques, a technique for extracting a changed component of a living organism and displaying the same by using as image processing difference extraction of video images whose operation can be performed at high speed has been studied.
This technique is described in Proceedings of 12-th Joint Conference on Medical Informatics (issued on November, 1992), pp. 77-78 and Proceedings of 32nd Conference on Japan Society of Medical Electronics and Biological Engineering (issued on May 1, 1993), pp. 218, for example.
In this technique, a continuous video moving picture including an object is continuously subtracted for each time difference to cancel information on an unchanged portion of the object and continuously extract and display only a changed component of the object.
Although the foregoing sensors are examples of the displacement sensor for extracting a changed component of an object, they have the following disadvantages.
Since the mechanical displacement sensor must be brought into direct contact with the object, although it is utilized in a displacement detector or the like in various types of plants, it cannot make measurements in a system whose direct contact with the object should be avoided.
Although the eddy current displacement sensor is utilized in detection of the level displacement of molten steel in molds in steel industry, for example, the relationship between the distance to the object and an output voltage must be previously examined in making measurements to adjust a zero span because an output value differs depending on the material of the object, and the object is limited to one causing an eddy current.
Although the laser displacement sensor is widely utilized for measurements of displacement, flow rates, distances, shapes and the like utilizing its high coherence, it requires a laser irradiating device which is a special light source high in cost and requiring care in treatment.
Although the ultrasonic displacement sensor has superior advantages that it is applied to various types of sensors developed utilizing the property of ultrasonic waves propagating in almost all media and particularly it can nonconstructively measure the internal state of a material, it has some disadvantages. For example, it requires an irradiating device, similarly to the laser displacement sensor, and it may not, in some cases, easily identify a portion to be measured because it cannot accurately recognize a space.
Although the computer vision is apparently similar to the present invention in that it can treat a moving picture, it basically forces particular points extracted from one or a plurality of images at the same time, that is, so-called stereoscopic vision or the like to be reconstructed (or restored) to three-dimensional space information. Accordingly, an algorithm or a circuit for finding an optimal solution become very complicated. In many cases, it is impossible not only to perform high-speed processing but also cause the optimal solution to diverge and obtain the practical precision because the computer vision has bad resistance to noises. Although the computer vision treats one or a plurality of images, it does not arrange in time series particular points, which are displayed on a CRT, for example, for each measurement, extracted from the images and treat the particular points as a time series signal.
Although the technique in the above described two articles, that is, Proceedings of 12th Joint Conference on Medical Informatics and Proceedings of 32nd Conference on Japan Society of Medical Electronics and Biological Engineering is a method of detecting a changed component of an object with high precision, the function is only output of a differential image and a measured value at a certain time point to a CRT or the like. For example, if the technique is applied to the diagnosis of abnormalities of a plant, an operator must always watch a CRT screen, which is not practical in terms of labor saving. Since the differential image is a differential image as a continuous moving picture but is not a time series signal as numeral data, the differential image cannot be treated as a time series signal by sampling using an ordinary analog-to-digital (A/D) converter. Since the hysteresis of various past data is not stored, difference between past hysteresis and present hysteresis are not recognized. Consequently, information is insufficient to apply the technique to the improvement in the precision of the diagnosis of abnormalities and the detection of abnormalities.